Open AccessResearch on risk prediction method of software robot based on artificial intelligence
Author(s) -
Zelun Kang
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2248/1/012003
Subject(s) - computer science , robot , software , artificial intelligence , identification (biology) , enhanced data rates for gsm evolution , edge detection , feature extraction , feature recognition , computer vision , machine learning , image (mathematics) , pattern recognition (psychology) , image processing , botany , biology , programming language
Aiming at the problem of software robot’s recognition of life scenes, this paper studies the recognition and judgment method based on AI edge computing. Based on artificial intelligence methods and the theory of edge computing, through the analysis of the overall architecture of edge computing, the scene judgment rules and recognition algorithms are clarified. Mainly, the feature extraction and recognition part of the software robot image recognition function is arranged in the edge server, so that the judgment and recognition can be quickly realized and the system operation efficiency can be improved. The experimental verification shows that: under the same conditions, the software robot identification error of the method in this paper is lower, and the calculation time is shorter than that of other software robots, which is far superior to the traditional identification method. At the same time, by changing the comparison of data receiving methods, it can also be proved that the use of edge computing is more efficient, and the recognition problems in the work of software robots can be realized.